Title :
Soil moisture extraction in sparse vegetated area using SAR and TM data
Author :
Wang, Cuizhen ; Qi, Jiaguo
Author_Institution :
Dept. of Geogr., Michigan State Univ., East Lansing, MI, USA
Abstract :
This study uses SAR/TM synergy to investigate the possibility of extracting soil moisture of vegetated areas. When the differential backscattering was used (σ0wet-σ0 dry), surface roughness was greatly reduced and the change in backscattering was primarily related to soil moisture and vegetation density. By modeling the Δσ0~NDVI relationship, soil moisture can be estimated with SAR and TM imagery. With and IEM model for bare soils, and soil moisture measurements, the authors deduced a series of moisture curves changing with Δσ 0 and NDVI. The range of soil moisture in test area is between 2.0% and 37.0%
Keywords :
geophysical signal processing; hydrological techniques; moisture measurement; radar signal processing; remote sensing; remote sensing by radar; sensor fusion; soil; synthetic aperture radar; IEM model; IR; SAR; TM; backscatter; differential backscattering; hydrology; infrared; measurement technique; multispectral remote sensing; radar remote sensing; radar scattering; soil moisture; sparse vegetated area; sparse vegetation; synthetic aperture radar; visible; Backscatter; Data mining; Moisture measurement; Radar; Rough surfaces; Soil measurements; Soil moisture; Surface roughness; Testing; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-6359-0
DOI :
10.1109/IGARSS.2000.858088
